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Record W4241542193 · doi:10.17725/rensit.2015.07.212

A QUARTER-CENTURY OF RUSSIAN ACADEMY OF NATURAL SCIENCES (five steps up)

2015· article· en· W4241542193 on OpenAlexaboutno aff
О. Л. Кузнецов

Bibliographic record

VenueRadioelectronics Nanosystems Information Technologies · 2015
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological Studies and Exploration
Canadian institutionsnot available
FundersLomonosov Moscow State UniversityBauman Moscow State Technical University
KeywordsQuarter (Canadian coin)Natural (archaeology)Natural scienceHistoryArchaeologyPhysicsAstronomy

Abstract

fetched live from OpenAlex

Summarized the history and formation of the largest Russian public expert organization -the Russian Academy of Natural Sciences, established a turning point for the country's 90 years of the 20th century.Marked and commented on the five stages of the development of the academy: the classic organization of sections, sections of gosprioritetam, thematic sections, regional sections and innovative sections.The motto of the Academy of Natural Sciences -interdisciplinarity and integration of diverse knowledge.The symbol of the Academy is the VI Vernadsky, the Academy is actively promoting Russian cosmism school.RANS initiate registration of scientific discoveries, is widely involved in the educational sector of the country, is the founder in 1994 of the University "Dubna", one of the best universities in the country for the recognition of experts.Publishing RANS -thousands of titles, the Bulletin of Natural Sciences, many sections and departments have their own magazines, including RENSIT.The Academy is widely recruited to participate in international forums (Summits), committees and festivals.As an all-Russian scientific organization, RANS plays an important role one of the cells of civil society, which is consolidating around a large domestic intellectual potential of performing a stabilizing role in the country.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.460
Threshold uncertainty score0.400

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.018
GPT teacher head0.223
Teacher spread0.205 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2015
Admission routes1
Has abstractyes

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